TY - GEN
T1 - Study on the prediction of patent hiding company using patent information analysis
AU - Kim, Youngho
AU - Lee, Junseok
AU - Kang, Jiho
AU - Park, Sangsung
AU - Jun, Sunghae
AU - Jang, Dongsik
N1 - Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A3B03031152). This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2017R1A2B1010208). This work was supported by the BK21 Plus (Big Data in Manufacturing and Logistics Systems, Korea University). This research was supported by the Commercialization Promotion Agency for R&D Outcomes(COMPA) funded by the Ministry of Science and ICT(MSIT).[2019K000305]
Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/8/23
Y1 - 2019/8/23
N2 - Establishment of an effective R&D strategy can be achieved through Prior art search. Prior art search is aimed at identifying major applicants in a specific technology field and is mainly carried out using patents. However, some companies hide their patents as M&A or other companies with most shares in order to avoid exposure. It is difficult to identify the actual owners of patents of such patent hiding companies. Thus, patent hiding companies hinder successful prior art search. To solve this problem, this paper proposes a model for predicting patent hiding companies by using text information and quantitative indicators of patents. As experimental data, N screen technology patents registered in USPTO are used. As a result of the experiment, Cleversafe was found to be IBM's patent hiding company.
AB - Establishment of an effective R&D strategy can be achieved through Prior art search. Prior art search is aimed at identifying major applicants in a specific technology field and is mainly carried out using patents. However, some companies hide their patents as M&A or other companies with most shares in order to avoid exposure. It is difficult to identify the actual owners of patents of such patent hiding companies. Thus, patent hiding companies hinder successful prior art search. To solve this problem, this paper proposes a model for predicting patent hiding companies by using text information and quantitative indicators of patents. As experimental data, N screen technology patents registered in USPTO are used. As a result of the experiment, Cleversafe was found to be IBM's patent hiding company.
KW - Latent Semantic Analysis
KW - Patent Hiding Company
KW - Patent Information Analysis
KW - Prior Art Search
UR - http://www.scopus.com/inward/record.url?scp=85074300419&partnerID=8YFLogxK
U2 - 10.1145/3357419.3357447
DO - 10.1145/3357419.3357447
M3 - Conference contribution
AN - SCOPUS:85074300419
T3 - ACM International Conference Proceeding Series
SP - 123
EP - 126
BT - ICICM 2019 - Proceedings of 2019 the 9th International Conference on Information Communication and Management
PB - Association for Computing Machinery
T2 - 9th International Conference on Information Communication and Management, ICICM 2019
Y2 - 23 August 2019 through 26 August 2019
ER -